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Mathematical and statistical methods
/*
* This file is part of the repicea library.
*
* Copyright (C) 2009-2012 Mathieu Fortin for Rouge-Epicea
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 3 of the License, or (at your option) any later version.
*
* This library is distributed with the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied
* warranty of MERCHANTABILITY or FITNESS FOR A
* PARTICULAR PURPOSE. See the GNU Lesser General Public
* License for more details.
*
* Please see the license at http://www.gnu.org/copyleft/lesser.html.
*/
package repicea.stats.model;
import repicea.math.Matrix;
import repicea.stats.estimators.Estimator;
/**
* This interface defines the services provided by a statistical model.
* @author Mathieu Fortin - October 2011
*/
public interface StatisticalModel {
/**
* Return the parameter estimates produced by the estimator.
* @return a Matrix instance
*/
public default Matrix getParameters() {
if (getEstimator().isConvergenceAchieved()) {
return getEstimator().getParameterEstimates().getMean();
} else {
throw new UnsupportedOperationException("The model parameters have not been estimated yet!");
}
}
/**
* This method returns the results of the fit on screen.
* @return a string containing the summary of the model fit
*/
public default String getSummary() {
StringBuilder sb = new StringBuilder();
sb.append(toString() + System.lineSeparator());
sb.append("Model definition : " + getModelDefinition() + System.lineSeparator() + System.lineSeparator());
sb.append(getEstimator().getReport() + System.lineSeparator());
return sb.toString();
}
/**
* This method computes the parameter estimates.
*/
public void doEstimation();
/**
* This method returns the model definition as entered by the user.
* @return a String
*/
public String getModelDefinition();
/**
* This method returns the optimizer of the log-likelihood function.
* @return an Optimizer instance
*/
public Estimator getEstimator();
}